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# Google Cloud Platform Gemini Enterprise Cloud Architect

- **Company:** InfoVision, Inc.
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Artificial Intelligence, Bash Shell, Cloud Computing Security, Cloud Engineering, Data Governance, Identity and Access Management, Python (Programming Language), Scripting, Google Cloud, Terraform
- **Published:** July 22, 2026
- **Apply:** https://www.dice.com/job-detail/62866600-f3de-4d77-96d6-4b289e148fb8

## About the Role

8+ years of experience in cloud architecture or solutions engineering, with substantial hands-on Google Cloud Platform experience
Demonstrated experience designing and deploying enterprise AI/agentic platforms (Gemini Enterprise, Vertex AI, or equivalent)
Proficiency with Infrastructure as Code (Terraform) and scripting (Python, Bash)
Solid understanding of cloud security, IAM, data governance, and responsible AI practices

## Description

This role architects and delivers enterprise-grade Google Cloud Platform (Google Cloud Platform) solutions centered on Gemini Enterprise, Google''s agentic AI platform for building, scaling, and governing enterprise agents. The architect partners with delivery, engineering, and client stakeholders to design secure, scalable cloud and agent architectures, working onsite in Dallas, TX. In the first 90 days, success looks like completing a current-state assessment of client cloud environments, standing up an initial Gemini Enterprise pilot or proof-of-concept agent, and establishing governance and security guardrails for agent deployment., Design and architect end-to-end Google Cloud Platform solutions that integrate the Gemini Enterprise Agent Platform for enterprise clients
Lead technology adoption of agentic AI capabilities, translating business requirements into scalable cloud and agent architectures
Build and maintain Infrastructure as Code (Terraform) for repeatable, auditable environment provisioning
Guide client stakeholders through migration and modernization strategies, evaluating design tradeoffs and rollout roadmaps
Collaborate with cross-functional engineering, data, and delivery teams to implement and scale enterprise-grade AI agents


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